Main Tab 1

Column

Column Tab 1

Column

Main Tab 2

Column

3. Example

p <-df %>%  ggplot(aes(x=preg)) + geom_bar()
ggplotly(p)

Column

Row 1

Main Tab 3


---
title: "Titanic"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    logo: logo.png
    source_code: embed
    social: menu
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(plotly)
library(knitr)
library(DT)
library(rsconnect)
# Create a ggplot object
library(plotly)
df <- read_csv('diabetes.csv')
df$preg <- case_when(df$Pregnancies >= 1 ~ "Has been Pregnant",TRUE ~"Never been pregnant")
```

{.sidebar}
=======================================================================

### 1. Titanic

The sinking of the Titanic is one of the most infamous shipwrecks in history. While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others.

### 2. Flexdashboard and Plotly

This interactive uses `flexdashboard` and `plotly` to visualize the data. 

Main Tab 1
=======================================================================

Column {data-width=500, .tabset}
-----------------------------------------------------------------------



### Column Tab 1

```{r}
datatable(df, options = list(
  pageLength = 25
))
```


Column {data-width=500}
-----------------------------------------------------------------------


```{r}
df %>% ggplot(aes(x=Age,y=Pregnancies))+geom_point()
```



Main Tab 2
=======================================================================

Column {data-width=500}
-----------------------------------------------------------------------



#### 3. Example

```{r, echo=TRUE, eval=TRUE}

p <-df %>%  ggplot(aes(x=preg)) + geom_bar()
ggplotly(p)
```



Column {data-width=500}
-----------------------------------------------------------------------

### Row 1

```{r}
p <- df %>% ggplot(aes(x=Age, y = Glucose)) + geom_point()
ggplotly(p)
```



Main Tab 3
=======================================================================

```{r}
df %>% ggplot(aes(x = SkinThickness, y = BloodPressure))+geom_point()
```